Getting people excited about their data one visual at a time™

I have discussed the use of Pie Charts and the Parts-to-Whole Relationship in a previous blog post. In that post, I noted some thoughts from Dr. Robert Kosara (photo, right).

Dr. Kosara is a research scientist at Tableau Software. His focus is on the communication of data through visualization and visual storytelling. Robert is also working on furthering our understanding of visual perception and cognition, so we can make data easier to understand and Tableau can develop new tools to communicate it more effectively.

His full list of publications can be found on his vanity website. Before joining Tableau in 2012, Robert was Associate Professor of Computer Science at The University of North Carolina at Charlotte. Robert received his M.Sc. and Ph.D. Degrees in Computer Science from Vienna University of Technology (Austria). In his copious spare time, Robert likes to run long distances and writing articles for his website, eagereyes.org.

In this post, I briefly discuss some of Dr. Kosara’s thought on the pie charts and the part-to-whole relationship, and show you the latest example from Fox New’s “What the Heck” department of parts-to-whole data visualizations.

Best regards,

Michael

The Pie Chart

Dr. Kosara contends that pie charts are perhaps the most ubiquitous chart type; they can be found in newspapers, business reports, and many other places. But few people actually understand the function of the pie chart and how to use it properly. In addition to issues stemming from using too many categories, the biggest problem is getting the basic premise: that the pie slices sum up to a meaningful whole.

Robert points out that the circle (the “pie”) represents some kind of whole, which is made up of the slices. What this means is that the pie chart first and foremost represents the size relationship between the parts and the entire thing. If a company has five divisions, and the pie chart shows profits per division, the sum of all the slices/divisions is the total profits of the company.

If the parts do not sum up to a meaningful whole, they cannot be represented in a pie chart, period. It makes no sense to show five different occupations in a pie chart, because there are obviously many missing. The total of such a subsample is not meaningful, and neither is the comparison of each individual value to the artificial whole.

Slices have to be mutually exclusive; by definition, they cannot overlap. The data therefore must not only sum up to a meaningful whole, but the values need to be categorized in such a way that they are not counted several times. A good indicator of something being wrong is when the percentages do not sum up to 100%, like in the infamous Fox News pie chart.

The 2017 Alabama Senate Race

In the data visualization above from Fox News, people were asked which potential candidate they were more likely to vote for in the upcoming Alabama Senate Race. Moore was favored 48.2% of the time and Jones was favored 56.6% of the time. Unfortunately, the categories are not mutually exclusive, and the chart makes no sense.

The Parts-to-Whole should equal 100%.

48.2% + 56.6% = 104.8%

For this data visualization to actually work, at the very least, Fox News should have shown the amount of overlap between the two candidates with a third category like “Unsure.” Given the size of the numbers (“The Parts”), and the fact the parts do not equal 100%, the chart is entirely meaningless.

When to Use Pie Charts (or Parts-to-Whole Relationships)

Dr. Kosara points out that there are some simple criteria that you can use to determine whether a pie chart is the right choice for your data.

Do the parts make up a meaningful whole? If not, use a different chart. Only use a pie chart if you can define the entire set in a way that makes sense to the viewer.

Are the parts mutually exclusive? If there is overlap between the parts, use a different chart.

Do you want to compare the parts to each other or the parts to the whole? If the main purpose is to compare between the parts, use a different chart. The main purpose of the pie chart is to show part-whole relationships.

How many parts do you have? If there are more than five to seven, use a different chart. Pie charts with lots of slices (or slices of very different size) are hard to read.

In all other cases, do not use a pie chart. The pie chart is the wrong chart type to use as a default; the bar chart is a much better choice for that. Using a pie chart requires a lot more thought, care, and awareness of its limitations than most other charts.